Evidence map›Paper›PMID 39138551›Full record

ArticleGenome medicine2024

Spatial multiomics reveals a subpopulation of fibroblasts associated with cancer stemness in human hepatocellular carcinoma.

Si-Yu Jing, Dan Liu, Na Feng, Hui Dong, He-Qi Wang, Xi Yan, Xu-Feng Chen, Min-Cheng Qu, Ping Lin, Bin Yi and 5 more

Abstract read
In one paragraph

Article in Genome medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

45 citing papers in PubMed.

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  8. Understanding how hypoxia contributes to liver cancer stem cells maintenance.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Si-Yu Jing *CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, People's Republic of China.ORCID 0000-0003-2910-4201
Dan Liu *Molecular Pathology Laboratory, National Center for Liver Cancer, Eastern Hepatobiliary Surgery Hospital, Shanghai, 201800, People's Republic of China.
Na Feng *Molecular Pathology Laboratory, National Center for Liver Cancer, Eastern Hepatobiliary Surgery Hospital, Shanghai, 201800, People's Republic of China.
Hui Dong *Department of Pathology, Eastern Hepatobiliary Surgery Hospital, Shanghai, 200438, People's Republic of China.
He-Qi WangCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, People's Republic of China.
Xi YanCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, People's Republic of China.
Xu-Feng ChenCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, People's Republic of China.
Min-Cheng QuMolecular Pathology Laboratory, National Center for Liver Cancer, Eastern Hepatobiliary Surgery Hospital, Shanghai, 201800, People's Republic of China.
Ping LinCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, People's Republic of China.
Bin YiDepartment of Organ Transplantation, Eastern Hepatobiliary Surgery Hospital, Shanghai, 201800, People's Republic of China.
Feiling FengDepartment of Biliary Tract Surgery I, Eastern Hepatobiliary Surgery Hospital, Shanghai, 201800, People's Republic of China.
Lei ChenNational Center for Liver Cancer and International Cooperation Laboratory On Signal Transduction, Eastern Hepatobiliary Surgery Institute/Hospital, Shanghai, 200438, People's Republic of China. chenlei@smmu.edu.cn.
Hong-Yang WangNational Center for Liver Cancer and International Cooperation Laboratory On Signal Transduction, Eastern Hepatobiliary Surgery Institute/Hospital, Shanghai, 200438, People's Republic of China. hywangk@vip.sina.com.
Hong LiCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, People's Republic of China. lihong01@sinh.ac.cn.
Yu-Fei HeMolecular Pathology Laboratory, National Center for Liver Cancer, Eastern Hepatobiliary Surgery Hospital, Shanghai, 201800, People's Republic of China. yfhe@sibcb.ac.cn.

Funding

CAS Youth Innovation Promotion Association 2018307Key Project of Jiading District Health Construction Commission of Shanghai 2020-ZD-01the Basic Medical Research Foundation of the Naval Medical University 2021MS15the Basic Medical Research Foundation of the Naval Medical University 2022yx005the National Key R&D Program of China 2021YFF1200900the National Natural Science Foundation of China 32170680the National Natural Science Foundation of China 81830054the National Natural Science Foundation of China 81972644the National Natural Science Foundation of China 81988101the National Natural Science Foundation of China 82372729the National Natural Science Foundation of China 91859205the National Natural Science Foundation of China T2122018the National Natural Science Foundation of China U21A20376the National Science and Technology Major Project of China 2018ZX10723204the National Science Foundation of Shanghai 21JC1406600the National Science Foundation of Shanghai 21XD1404600the National Science Foundation of Shanghai 22140901000
6 · The paper itself

Abstract

backgroundCancer-associated fibroblasts (CAFs) are the prominent cell type in the tumor microenvironment (TME), and CAF subsets have been identified in various tumors. However, how CAFs spatially coordinate other cell populations within the liver TME to promote cancer progression remains unclear.

methodsWe combined multi-region proteomics (6 patients, 24 samples), 10X Genomics Visium spatial transcriptomics (11 patients, 25 samples), and multiplexed imaging (92 patients, 264 samples) technologies to decipher the expression heterogeneity, functional diversity, spatial distribution, colocalization, and interaction of fibroblasts. The newly identified CAF subpopulation was validated by cells isolated from 5 liver cancer patients and in vitro functional assays.

resultsWe identified a liver CAF subpopulation, marked by the expression of COL1A2, COL4A1, COL4A2, CTGF, and FSTL1, and named F5-CAF. F5-CAF is preferentially located within and around tumor nests and colocalizes with cancer cells with higher stemness in hepatocellular carcinoma (HCC). Multiplexed staining of 92 patients and the bulk transcriptome of 371 patients demonstrated that the abundance of F5-CAFs in HCC was associated with a worse prognosis. Further in vitro experiments showed that F5-CAFs isolated from liver cancer patients can promote the proliferation and stemness of HCC cells.

conclusionsWe identified a CAF subpopulation F5-CAF in liver cancer, which is associated with cancer stemness and unfavorable prognosis. Our results provide potential mechanisms by which the CAF subset in the TME promotes the development of liver cancer by supporting the survival of cancer stem cells.

Indexed as

Cancer-Associated FibroblastsCarcinoma, HepatocellularLiver NeoplasmsNeoplastic Stem CellsTumor MicroenvironmentCell Line, TumorCell ProliferationGene Expression ProfilingGene Expression Regulation, NeoplasticGenomicsHumansMultiomicsPrognosisProteomicsTranscriptomeCancer-associated fibroblastCancer stem cellLiver cancerSpatial transcriptomicsTumor microenvironment

Identifiers

PMID39138551
PMCPMC11320883

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.